Literature DB >> 12386111

Defining and improving data quality in medical registries: a literature review, case study, and generic framework.

Danielle G T Arts1, Nicolette F De Keizer, Gert-Jan Scheffer.   

Abstract

Over the past years the number of medical registries has increased sharply. Their value strongly depends on the quality of the data contained in the registry. To optimize data quality, special procedures have to be followed. A literature review and a case study of data quality formed the basis for the development of a framework of procedures for data quality assurance in medical registries. Procedures in the framework have been divided into procedures for the co-ordinating center of the registry (central) and procedures for the centers where the data are collected (local). These central and local procedures are further subdivided into (a) the prevention of insufficient data quality, (b) the detection of imperfect data and their causes, and (c) actions to be taken / corrections. The framework can be used to set up a new registry or to identify procedures in existing registries that need adjustment to improve data quality.

Mesh:

Year:  2002        PMID: 12386111      PMCID: PMC349377          DOI: 10.1197/jamia.m1087

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


  38 in total

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Journal:  J Am Med Inform Assoc       Date:  2000 Jan-Feb       Impact factor: 4.497

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Authors:  G J Prud'homme; P L Canner; J A Cutler
Journal:  Control Clin Trials       Date:  1989-09
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  129 in total

1.  Effectiveness of classroom based crew resource management training in the intensive care unit: study design of a controlled trial.

Authors:  Peter F Kemper; Martine de Bruijne; Cathy van Dyck; Cordula Wagner
Journal:  BMC Health Serv Res       Date:  2011-11-10       Impact factor: 2.655

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Authors:  Stefan Mathis-Edenhofer; Brigitte Piso
Journal:  Wien Med Wochenschr       Date:  2011-12

3.  End-user support for primary care electronic medical records: a qualitative case study of users' needs, expectations and realities.

Authors:  Aviv Shachak; Catherine Montgomery; Rustam Dow; Jan Barnsley; Karen Tu; Alejandro R Jadad; Louise Lemieux-Charles
Journal:  Health Syst (Basingstoke)       Date:  2013-11-01

Review 4.  Treatment decisions in multiple sclerosis - insights from real-world observational studies.

Authors:  Maria Trojano; Mar Tintore; Xavier Montalban; Jan Hillert; Tomas Kalincik; Pietro Iaffaldano; Tim Spelman; Maria Pia Sormani; Helmut Butzkueven
Journal:  Nat Rev Neurol       Date:  2017-01-13       Impact factor: 42.937

5.  Analyzing the effect of data quality on the accuracy of clinical decision support systems: a computer simulation approach.

Authors:  Sharique Hasan; Rema Padman
Journal:  AMIA Annu Symp Proc       Date:  2006

6.  Establishing a Multicentre Trauma Registry in India: An Evaluation of Data Completeness.

Authors:  Gowri Shivasabesan; Gerard M O'Reilly; Joseph Mathew; Mark C Fitzgerald; Amit Gupta; Nobhojit Roy; Manjul Joshipura; Naveen Sharma; Peter Cameron; Madonna Fahey; Teresa Howard; Zoe Cheung; Vineet Kumar; Bhavesh Jarwani; Kapil Dev Soni; Pankaj Patel; Advait Thakor; Mahesh Misra; Russell L Gruen; Biswadev Mitra
Journal:  World J Surg       Date:  2019-10       Impact factor: 3.352

7.  Redesign of diagnostic coding in pediatrics: from form-based to discharge letter linked.

Authors:  Hilco Prins; Hans Büller; Betty Zwetsloot-Schonk
Journal:  Perspect Health Inf Manag       Date:  2004-12-07

8.  Analysis of data errors in clinical research databases.

Authors:  Saveli I Goldberg; Andrzej Niemierko; Alexander Turchin
Journal:  AMIA Annu Symp Proc       Date:  2008-11-06

9.  Electronic health records based phenotyping in next-generation clinical trials: a perspective from the NIH Health Care Systems Collaboratory.

Authors:  Rachel L Richesson; W Ed Hammond; Meredith Nahm; Douglas Wixted; Gregory E Simon; Jennifer G Robinson; Alan E Bauck; Denise Cifelli; Michelle M Smerek; John Dickerson; Reesa L Laws; Rosemary A Madigan; Shelley A Rusincovitch; Cynthia Kluchar; Robert M Califf
Journal:  J Am Med Inform Assoc       Date:  2013-08-16       Impact factor: 4.497

10.  A modified real AdaBoost algorithm to discover intensive care unit subgroups with a poor outcome.

Authors:  Antonie Koetsier; Nicolette F de Keizer; Ameen Abu-Hanna; Niels Peek
Journal:  AMIA Annu Symp Proc       Date:  2013-11-16
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